Not sure how the featuresets compare but AWS is releasing materialized views for Redshift sometime soon and one of the things it will support is incremental refresh (assuming your view meets some criteria).
I'm sure Materialize is better at this since it's purpose-built but if you're on Redshift you can get at least some of the benefits of incremental materialize.
Materialized views, the upcoming ability to query directly from an RDS transactional DB through Redshift, and finally true separation of compute vs storage with RA nodes IMO make Redshift the market leader by a huge margin now. I haven't actually tested RA nodes yet, but if performance is even just a fraction of legacy nodes then the competition is already dead. Redshift already is one of the best engines to optimize a query
It's been a while since I've used Redshift, but isn't it still dependent on data coming in via a COPY from S3? Any sort of Redshift materialized view offering would depend on batches of data landing in an underlying table or tables. The closest service offering from AWS is probably using Kinesis analytics (or Flink on KA) using their flavor of streaming SQL to join Kinesis streams forming new ones.
With the introduction of Spectrum you can back a Redshift table with data in S3 directly. I'm not sure how that interacts with the materialized views though. Probably not supported yet but I would expect it to be eventually.
I'm sure Materialize is better at this since it's purpose-built but if you're on Redshift you can get at least some of the benefits of incremental materialize.